code: def autograd(f, ds, points):
      """Evaluate derivatives of f on the given points."""
      df_ds = lambda *args: f(np.stack(args, axis=-1))
      for i in ds:
          df_ds = egrad(df_ds, i)
      ndim = points.shape[-1]
      return df_ds(*[points[..., i] for i in range(ndim)])
  
file_path: tf-quant-finance/tf_quant_finance/experimental/finite_difference/methods.py
imports: from autograd import elementwise_grad
  import autograd.numpy
  import pandas
  import sobol_seq
label_desc: Use image node_id 4 for calling a global function with example usage: autograd(f, ds, points) and returns: df_ds